• Journal of the Korean Society of Child Welfare
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• no.27
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• pp.95-120
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• 2008

The purpose of this study is to investigate the impact of family resilient factors on the adaption of families with child with chronic disease. The study sample consisted 287 families with chronic illness child. The survey was done from July 1. 2007 to October 31. 2007. It was analysed that the effect of families resilience through structural equation model. Adequate fitness of the model was observed. The family resilience of families with chronic illness child has significantly positive effect on the family adaptation. Family stress had negative effect on family hardiness. Family hardiness had positive effect on family communication, and family communication had positive effect on social support. Social support had positive effect on family adaptation. According to this finding, intervention strategies focusing on in creasing resilient factors were suggested.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.316-316
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• 2016

HyGIS는 DEM 기반의 수문지형처리를 중심으로 다양한 모형을 연계할 수 있도록 구성된 S/W 모음이다. 이는 한국건설기술연구원을 비롯한 다수의 기관 및 연구원들이 노력한 성과물이다. 본 연구는 기존 HyGIS 연구과정에서 도출된 성과물의 실용화 사업화를 위한 방안을 연구하였다. 이를 위하여 S/W 테스팅, 오픈소스 도입, 클라우드 컴퓨팅으로 나누어 접근하였다. 먼저 S/W의 테스팅에 있어서 기존 개발 소스코드는 블랙박스 테스트 방식의 동등 클래스 분할, 경계 값 분석 등 일부 모듈에 대한 단위 테스트와 제한적인 통합테스트가 수행된 바 있다. 보다 체계적인 테스트 단계로서 화이트박스 테스트 개념 중 문장/분기/조건 커버리지에 대하여 검토하였으며, 실제 소스코드 중 핵심 구간에 대한 적용 및 정량화를 통하여 현 수준을 객관적으로 진단하였고 보완 방안을 도출하였다. 오픈소스 적용을 위하여 QGIS, MapWindow 등 공간정보 분야의 최신 오픈소스 모듈을 비교 검토하였다. 적용 단계는 이를 기존 HyGIS S/W에 반영시키는 과정이며, S/W 관점에서는 컴포넌트 모듈의 대체라고 표현될 수 있다. 대규모의 전환 비용이 발생되므로 적용 후보에 대하여는 기능적 측면 뿐만 아니라 마이그레이션 비용과 중장기적인 유지보수 비용을 고려한 검토가 이루어 졌다. 한편 오픈소스 기술의 적용은 단순히 구성 요소 원가절감 측면만이 아닌, 중장기적 유지보수 체계 도모 및 지속가능한 생태계로의 전환에 더 큰 의의가 있다. 마지막으로 클라우드 컴퓨팅 기술의 적용 분야이다. HyGIS 입력 Data의 공급을 위한 인프라로서 자체 구축 인프라가 아닌 IaaS 클라우드인 Blob Storage 및 CDN을 시험 적용하였다. 클라우드를 활용함으로써 초기 비용을 최소화하고 합리적 비용으로 유연한 확장이 가능한(Scale Out, Scale Up) 구조를 취하게 되었다. 또한 입력 Data 공급 서버를 위한 Storage 측면만이 아니라 S/W의 배포에 있어서도 클라우드 컴퓨팅 기술을 활용하고자 시도하였다. 클라우드 기술을 활용하여 HyGIS S/W가 설치된 VM(Virtual Machine)자체를 임대하는 방식으로 시험 구성 되었다. VM에 대한 RDP 프로토콜 Access에 있어서 IP기반 접근 제어를 통하여 보안을 강화하는 방안을 실험하였으며, ISO 27001, ISO 27018 등 관련 보안 규정에 부합하는 서비스 제공이 가능하도록 검토하였다. 이러한 클라우드 VM방식 서비스를 통하여 Package형 S/W 뿐만 아니라 Subscription 방식의 서비스 제공 방식을 병행할 수 있다. 사용자에게는 S/W 설치 및 H/W Lock 구비 과정이 생략되는 이점이 있다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.6
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• pp.1585-1594
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• 2018

In recent years The importance of information security management for securing information collection and analysis, production and distribution is increasing. Companies are assured of confidence in information security through authentication of information Security Management System. However, level assessment and use of domains that make up the management system is limited. On the other hand, the security maturity model is able to diagnose the level of information protection of the enterprise step by step. It is also possible to judge the area to be improved urgently. It is a tool to support goal setting according to the characteristics and level of company. In this paper, C2M2, which is an example of security maturity model, is compared and analyzed with Korea Information Security Management System certification. Benchmark the model to check the level of information security management and derive the priority among the items that constitute the detailed area of information security measures of ISMS certification. It also look at ways to check the level of information security management step by step.

• Journal of Technology Innovation
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• v.26 no.4
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• pp.173-198
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• 2018

In this paper, we analyze the determinants of the adoption of industrial robots using the data from 42 countries, and thereby examine the factors underlying the rapid expansion of industrial robots in Korea. To this end, the industrial robot data for the years 2001-2016 were drawn from the World Robotics dataset of the International Federation of Robotics (IFR). The explanatory variables included labor market environment variables and innovation capacity variables extracted from the dataset of the relevant international organizations. For data analysis, the Arellano-Bond dynamic panel analysis was performed to control for the endogeneity problem of some explanatory variables. The empirical results confirmed the exceptionally rapid expansion of industrial robots in Korea as compared to other countries, even when considering the national income level, employment cost, and innovation capacity. This phenomenon could be attributed to both the demand-side and supply-side factors. For one thing, changes in the labor market environment, such as an increase in employment costs, have led to an increase of the corporate demand for industrial robots. For another, the supply-side factors, such as an increase in the capital intensity and innovation capacity of companies, have also contributed to the widespread adoption of industrial robots.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.4
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• pp.183-189
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• 2021

In recent years, active research has been devoted toward developing a monitoring system using ambient vibration data in order to quantitatively determine the deterioration occurring in a structure over a long period of time. This study developed a low-cost edge computing system that detects the abnormalities in structures by utilizing the dynamic characteristics acquired from the structure over the long term for ensemble learning. The system hardware consists of the Raspberry Pi, an accelerometer, an inclinometer, a GPS RTK module, and a LoRa communication module. The structural abnormality detection afforded by the ensemble learning using dynamic characteristics is verified using a laboratory-scale structure model vibration experiment. A real-time distributed processing algorithm with dynamic feature extraction based on the experiment is installed on the Raspberry Pi. Based on the stable operation of installed systems at the Community Service Center, Pohang-si, Korea, the validity of the developed system was verified on-site.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.4
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• pp.510-518
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• 2022

The diagnostic evaluation conducted at the national level is very important to detect underachievers in school early. This study used an artificial intelligence method to find the characteristics of underachievers that affect learning development for middle school students. In this study an artificial intelligence model was constructed and analyzed to determine whether the Busan Education Longitudinal Data in 2020 by entering data from the first year of middle school in 2019. A predictive model was developed to predict basic middle school Korean, English, and mathematics education with machine learning algorithms, and it was confirmed that the accuracy was 78%, 82%, and 83%, respectively, in the prediction for the next school year. In addition, by drawing an achievement prediction decision tree for each middle school subject we are analyzing the process of prediction. Finally, we examined what characteristics affect achievement prediction.

• Journal of Family Resource Management and Policy Review
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• v.26 no.3
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• pp.19-34
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• 2022

There are growing concerns about debt insolvency among youth and low-income households. The deterioration in household debt quality among young people is due to a combination of sluggish employment, an increase in student loan burden and an increase in high-interest loans from the secondary financial sector. The purpose of this study was to explore the possibility of household debt default among young borrowers in Korea and to predict the factors affecting this possibility. This study utilized the 2021 Household Finance and Welfare Survey and used random forest algorithm to comprehensively analyze factors related to the possibility of default risk among young adults. This study presented the importance index and partial dependence charts of major determinants. This study found that the ratio of debt to assets(DTA), medical costs, household default risk index (HDRI), communication costs, and housing costs the focal independent variables.

• Journal of the Korea Convergence Society
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• v.12 no.5
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• pp.255-266
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• 2021

This descriptive survey aimed to investigate the health promotion behaviors of patients with reflux esophagitis and identify the factors influencing it using the health promotion model. The survey was conducted with 178 outpatients diagnosed with reflux esophagitis at C university hospital. Data were analyzed by descriptive statistics, t-test, ANOVA, Pearson's correlation, and multiple regression using SPSS win ver 20. We found that alcohol consumption, BMI, perceived benefit, internal control level, and perceived health status of the patients are significant factors influencing health promotion behavior. The explanatory power was 49%. Therefore, this study is consistent with previous studies that elucidated that changing lifestyle behaviors and obesity control are necessary to alleviate reflux esophagitis. Based on these findings, we propose to develop and apply an educational program for evaluation.

• Journal of Advanced Navigation Technology
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• v.27 no.1
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• pp.111-118
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• 2023

For the implementation of a smart factory, it is necessary to collect data by connecting various sensors and devices in the manufacturing environment and to diagnose or predict failures in production facilities through data analysis. In this paper, to predict the residual useful lifetime of milling insert used for machining products in CNC machine, weight k-NN algorithm, Decision Tree, SVR, XGBoost, Random forest, 1D-CNN, and frequency spectrum based on vibration signal are investigated. As the results of the paper, the frequency spectrum does not provide a reliable criterion for an accurate prediction of the residual useful lifetime of an insert. And the weighted k-nearest neighbor algorithm performed best with an MAE of 0.0013, MSE of 0.004, and RMSE of 0.0192. This is an error of 0.001 seconds of the remaining useful lifetime of the insert predicted by the weighted-nearest neighbor algorithm, and it is considered to be a level that can be applied to actual industrial sites.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1223-1234
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• 2022

Efforts for reducing greenhouse gas emission coping with climate change have also been performed in the field of water and wastewater works. In particular, the technical development for reducing energy has been applied in operating water distribution system. The reduction of energy in water distribution system can be achieved by reducing structural loss induced by topographic variation and operational loss induced by leakage and friction. However, both analytical and numerical approaches for analyzing energy budget of water distribution system has been challengeable because energy components are affected by the complex interaction of affecting factors. This research drew mathematical equations for 5 types of state (hypothetical, ideal, leak-included ideal, leak-excluded real, and real), which depend on the assumptions of topographic variation, leakage, and friction. Furthermore, the derived equations are schematically illustrated and applied into simple water network. The suggested method makes water utilities quantify, classify, and evaluate the energy of water distribution system.